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Tecniche vHTS per il Drug Design

Tecniche vHTS per il Drug Design. Drug Discovery is:. interdisciplinary expensive time-consuming. Drug Discovery is:. Single new drug: $880 million 15 years development. Survey of about 50 companies. Disease target identification. Discovery and optimization

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Tecniche vHTS per il Drug Design

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  1. Tecniche vHTS per il Drug Design

  2. Drug Discovery is: • interdisciplinary • expensive • time-consuming

  3. Drug Discovery is: Single new drug: $880 million 15 years development Surveyofabout 50 companies • Disease target identification • Discovery and optimization of lead structures • Clinical tests and approval 75% efforts lost due to failures!

  4. Outline: 1. Cheminformatics: vHTS 2. Bioinformatics: Systemic approaches In silico Drug Discovery • Bioinformatics: biological target identification and validation • Cheminformatics: search for and optimization of chemical lead structures • Cost saving: $130 million • Time saving: 0.8 years

  5. Flexibility • Cost-effectiveness • Speed In Silico vHTS Real vs. In Silico HTS

  6. vHTS Principle of similarity Principle of complementarity vHTS: modelling molecular recognition • Highly sophisticated way to query databases • Strongly simplified simulation of high-throughput screening essays

  7. vHTS: principle of similarity (ligand based) If one or more active compounds are known Search databases for more potent molecules Three categories: • Alignment / Superimposition • Pharmacophore modeling • Quantitative structure-activity relationship (QSAR)

  8. Ligand-based methods: Alignment Single 3D structure as a template Superpositioning and scoring of molecules from databases Scoring: steric and physicochemical properties

  9. Ligand-based methods: Pharmacofores A pharmacophore is the 3D arrangement of chemical groups that is required for the biological activity of a molecule Generated from a series of known active compounds Database-search for molecules that fulfill the specified geometrical constraints

  10. Metodi Ligand Based: QSAR QSAR methods are statistical approaches that correlate biological data with molecular descriptors to derive QSAR models. QSAR models are then used to predict the activity of novel compounds

  11. vHTS Principle of similarity Principle of complementarity vHTS: modelling molecular recognition • Highly sophisticated way to query databases • Strongly simplified simulation of high-throughput screening essays

  12. Drug Design and Structural Genomics 72717structures(27 April 2011)

  13. vHTS: principle of complementarity (receptor based) Knowledge of the receptor 3D structure allows… …screening for molecules that fit the active site Receptor Based Methods: Docking

  14. Metodi Receptor Based: Docking 3D Structure Determination Site Representation Site Identification/Characterization Ligand Generation Docking De Novo Design Scoring DGbind = DGcomplex – (DGligand – DGreceptor) DGbind = -RT ln Keq = -RT ln Kd

  15. Metodi Receptor Based: Docking Problem 1: PES sampling • Receptor flexibility: • Difficult to predict from X-ray data • Computationally unfeasible in HTS • Ligand flexibility Problem 2: Scoring and rankings • Computational time limits (vHTS) • Empirical forcefield • Consensus scoring

  16. Our job: Sampling the PES ofmolecules Energia di una molecola in funzione delle coordinate atomiche • minimi: conformazioni • punti sella: stati di transizione

  17. QM-basedmethods • QM methods are based on the followingprinciples: • Nuclei and electrons are distinguishedfromeachother. • Electron-electron (usuallyaveraged) and electron-nuclearinteractions are explicit. • Interactions are governedbynuclear and electron charges (i.e. potentialenergy) and electron motions. Interactionsdetermine the spatialdistribution of nuclei and electrons and theirenergies.

  18. MM-basedmethods MMmethods are based on the followingprinciples: Nuclei and electrons are lumpedintoatom-likeparticles. Atom-likeparticles are spherical and have a net charge. Interactions are based on springs and classicalpotentials. Interactionsmustbepreassignedtospecificsetsofatoms. Interactionsdetermine the spatialdistributionof atom-likeparticles and theirenergies.

  19. Adsorption • Distribution • Metabolism • Excretion • Toxicity ADMET • Full power of in silico screening of large databases: • Integration of virtual molecular recognition with… • …filter algorithms for ADMET

  20. Conclusions: what really is vHTS? It is not: • the recipe to discover a new drug • a single method • a stand-alone approach It is: • a tool to drive rational screening • the integration of several methods • a key actor in drug discovery

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